BioMed Research International / 2021 / Article / Tab 3

Research Article

An Interpretable Model-Based Prediction of Severity and Crucial Factors in Patients with COVID-19

Table 3

The AUC, sensitivity, and specificity comparisons.

AUC (95% CI)Sensitivity (95% CI)Specificity (95% CI)

LR0.891 (0.783, 0.956)90.91 (58.7, 99.8)93.88 (83.1, 98.7)0.1306
KNN0.857 (0.743, 0.934)100.00 (71.5, 100.0)61.22 (46.2, 74.8)0.2844
DT0.707 (0.575, 0.817)45.45 (16.7, 76.6)95.92 (86.0, 99.5)0.0095
RF0.907 (0.804, 0.967)90.91 (58.7, 99.8)95.92 (86.0, 99.5)0.1915
SVM0.892 (0.785, 0.958)90.91 (58.7, 99.8)91.84 (80.4, 97.7)0.2006
XGBoost0.924 (0.826, 0.976)90.91 (58.7, 99.8)97.96 (89.1, 99.9)

Two-sided values were calculated by comparing AUC for the XGBoost model with the other models. AUC comparisons were evaluated using the DeLong test; LR: logistic regression; KNN: -nearest neighbor; DT: decision tree; RF: random forest; SVM: support vector machine; XGBoost: eXtreme gradient boosting.

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